The Syncfusion Big Data Platform

There has been a virtual explosion in the amount of data being created. Not very long ago, transactional information was the main source of data. In the past, only a few large organizations accumulated unwieldy amounts of transactional data. The need to store and process such amounts of data, was not a common business requirement for most organizations.

The situation has changed dramatically. Organizations have woken up to the reality that huge amounts of data are being generated on a daily basis by people and machines.

Storage and Analysis of Big Data

Though most organizations have realized that they are accumulating more data than ever before, only a minority have implemented a storage and analysis strategy for such data. There is good reason for this. The storage of transactional data in relational database systems has been well understood for several decades. The tools that are used for this purpose, such as SQL Server and Oracle, are well understood. Relational data is stored in a highly structured format and processed using SQL. The warehousing of this data to build online analytical processing (OLAP) systems is also understood well.

On the other hand, unstructured data, especially in huge quantities, is, by nature, very different. It has no predefined structure. Relational databases are not suitable for storing such data. Storage, on traditional file systems, is also problematic, since the size of the data often exceeds the capabilities of a single machine.

Apache Hadoop

Hadoop has gained broad acceptance as an effective storage and processing mechanism for big data. Hadoop is an open-source implementation of systems that Google implemented internally, to solve big data problems related to storing indexes for web scale data.

One way to think of Hadoop is that it enabled us to group several machines together in a cluster and treat the resulting unit as one logical unit. This allows us to process data on a scale far more than any of the nodes could handle directly. Additionally processing data in this manner is not just about dealing with scale. It instead marks a shift from just obtaining insights from relational data to obtaining powerful insights from all your data.

The Syncfusion Big Data platform

The Syncfusion Big Data platform is a user friendly platform for working with big data on Windows and Linux. It has two key components.

Syncfusion Big Data Studio

  • Interactive Big Data environment for Windows.
  • Connect and work with Hadoop cluster running in Windows and Linux.
  • Includes developer edition of Apache Hadoop for offline development.
  • Can connect to local and remote cluster.

Syncfusion Big Data Cluster Manager

  • User friendly production cluster implementation that is optimized for Windows and Linux.
  • Install a complete production cluster on Windows and Linux in minutes.
  • Deploy cluster in Microsoft Azure virtual machines environment in minutes.
  • Manage and monitor multiple Hadoop cluster at a time.

Additional help resources

  • The Knowledge Base section contains responses to some of the most common questions that other customers have asked us in the past so this would be a good place to search for topics that are not covered in the user guide.

  • Similar to the Knowledge Base, the forum section also contains responses to questions that other customers have asked us in the past.

Create a support incident

If you are still not able to find the information that you are looking for in the self-help resources mentioned above then please contact us by creating a support ticket.